[1]崔铁军,郭大龙.基于改进YOLOX的变电站工人防护设备检测研究[J].中国安全生产科学技术,2023,19(4):201-206.
CUI Tiejun,GUO Dalong.Research on detection of substation worker protective equipment based on improved YOLOX[J].Journal of Safety Science and Technology,2023,19(4):201-206.
[2]葛军凯,史令彬.现代科技在电力安全管理中的应用策略——评《电力安全风险管理》[J].中国安全生产科学技术,2021,17(7):191-191.
GE Junkai,SHI Lingbin.Application strategy of modern technology in power safety management-review of “power safety risk management”[J].Journal of Safety Science and Technology,2021,17(7):191-191.
[3]余光凯,刘庭,刘凯,等.面向协作机械臂的10 kV配网带电作业安全距离研究及绝缘设计[J].高电压技术,2023,49(9):3936-3945.
YU Guangkai,LIU Ting,LIU Kai,et al.Research on safety distance and insulation design of 10 kV distribution line live working robot based on cooperative manipulator[J].High Voltage Engineering,2023,49(9):3936-3945.
[4]常政威,彭倩,陈缨.基于机器学习和图像识别的电力作业现场安全监督方法[J].中国电力,2020,53(4):155-160.
CHANG Zhengwei,PENG Qian,CHEN Ying.Safety supervision method for power operation site based on machine learning and image recognition[J].Electric Power,2020,53(4):155-160.
[5]王波,董礼,林勇,等.基于SENet-SSD的水电厂人员作业安全行为识别方法研究[J].水电与新能源,2023,37(2):26-29.
WANG Bo,DONG Li,LIN Yong,et al.On the identification of safety operation behaviors of personnel in hydropower plants based on SENet-SSD[J].Hydropower and New Energy,2023,37(2):26-29.
[6]SONG L C,YU G,YUAN J S,et al.Human pose estimation and its application to action recognition:a survey[J].Journal of Visual Communication and Image Representation,2021,76:103055.
[7]LINDEBERG T.Scale invariant feature transform[J].Scholarpedia,2012,7(5):10491.
[8]卢颖,吕希凡,郭良杰,等.基于Kinect的地铁乘客不安全行为识别方法与实验[J].中国安全生产科学技术,2021,17(12):162-168.
LU Ying,LYU Xifan,GUO Liangjie,et al.Kinect-based recognition method and experiments on unsafe behavior of subway passengers[J].Journal of Safety Science and Technology,2021,17(12):162-168.
[9]赵小虎,黄程龙.基于Kinect的矿井人员违规行为识别算法研究[J].湖南大学学报(自然科学版),2020,47(4):92-98.
ZHAO Xiaohu,HUANG Chenglong.Research on identification algorithm of mine person’s violation behavior based on kinect[J].Journal of Hunan University(Natural Sciences),2020,47(4):92-98.
[10]马双双,王佳,曹少中,等.基于深度学习的二维人体姿态估计算法综述[J].计算机系统应用,2022,31(10):36-43.
MA Shuangshuang,WANG Jia,CAO Shaozhong,et al.Overview on two-dimensional human pose estimation methods based on deep learning[J].Computer Systems & Applications,2022,31(10):36-43.
[11]FANG H S,XIE S Q,TAI Y W,et al.Rmpe:regional multi-person pose estimation[C]//Proceedings of the 2017 IEEE International Conference on Computer Vision(ICCV).USA:IEEE,2017:2353-2362.
[12]CAO Z,HIDALGO G,SIMON T,et al.OpenPose:realtime multi-person 2d pose estimation using part affinity fields[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2021,43(1):172-186.
[13]KE Q H,BENNAMOUN M,AN S J,et al.A new representation of skeleton sequences for 3D action recognition[C]//2017 IEEE Conference on Computer Vision and Pattern Recognition(CVPR),USA:IEEE,2017:4570-4579.
[14]YAN S,XIONG Y,LIN D.Spatial temporal graph convolutional networks for skeleton-based action recognition[C]//32nd AAAI Conference on Artificial Intelligence (AAAI),2018:7444-7452.
[15]苏超,王国中.基于改进OpenPose的学生行为识别研究[J].计算机应用研究,2021,38(10):3183-3188.
SU Chao,WANG Guozhong.Research on student behavior recognition based on improved OpenPose[J].Application Research of Computers,2021,38(10):3183-3188.
[16]LI S,FANG Z,SONG W F,et al.Bidirectional optimization coupled lightweight networks for efficient and robust multi-person 2D pose estimation[J].Journal of Computer Science and Technology,2019,34:522-536.
[17]HOWARD A G,ZHU M L,CHEN B,et al.MobileNets:efficient convolutional neural networks for mobile vision applications[J].International Journal of Computer Vision,2017,8(17):12670695.
[18]孔玮,刘云,李辉,等.基于图卷积网络的行为识别方法综述[J].控制与决策,2021,36(7):1537-1546.
KONG Wei,LIU Yun,LI Hui,et al.A survey of action recognition methods based on graph convolutional network[J].Control and Decision,2021,36(7):1537-1546.
[19]饶天荣,潘涛,徐会军.基于交叉注意力机制的煤矿井下不安全行为识别[J].工矿自动化,2022,48(10):48-54.
RAO Tianrong,PAN Tao,XU Huijun.Unsafe action recognition in underground coal mine based on cross-attention mechanism[J].Journal of Mine Automation,2022,48(10):48-54.
[20]游越,伊力哈木·亚尔买买提.基于改进YOLOv5在电力巡检中的目标检测算法研究[J].高压电器,2023,59(2):89-96.
YOU Yue,YILIHAMU Yaermaimaiti.Research on target detection algorithm based on improved YOLOv5 in power patrol inspection[J].High Voltage Apparatus,2023,59(2):89-96.
[21]HU J,SHEN L,ALBANIE S,et al.Squeeze-and-excitation networks[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2020,42(8):2011-2023.
[22]张蔚澜,齐华,李胜.时空图卷积网络在人体异常行为识别中的应用[J].计算机工程与应用,2022,58(12):122-131.
ZHANG Weilan,QI Hua,LI Sheng.Application of spatial temporal graph convolutional networks in human abnormal behavior recognition[J].Computer Engineering and Applications,2022,58(12):122-131.
[23]王超,徐楚昕,董杰,等.基于ST-GCN的空中交通管制员不安全行为识别[J].中国安全科学学报,2023,33(5):42-48.
WANG Chao,XU Chuxin,DONG Jie,et al.Unsafe behavior recognition of air traffic controllers based on ST-GCN[J].China Safety Science Journal,2023,33(5):42-48.
[1]高玉坤,冯芊,王皖,等.10 kV带电作业风险评估模型构建与应用研究*[J].中国安全生产科学技术,2024,20(7):208.[doi:10.11731/j.issn.1673-193x.2024.07.028]
GAO Yukun,FENG Qian,WANG Wan,et al.Research on construction and application of risk assessment model for 10kV live working[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2024,20(9):208.[doi:10.11731/j.issn.1673-193x.2024.07.028]